What is the focus of 'Practical Deep Learning: A Python-Based Introduction'?

The book primarily focuses on providing a hands-on guide to deep learning using Python. It emphasizes practical implementation over theoretical concepts, allowing readers to learn through real-world examples. This approach is particularly beneficial for programmers and data scientists looking to apply deep learning in various projects, such as image recognition or natural language processing.

Who is the target audience for this book?

The intended audience includes aspiring data scientists, machine learning enthusiasts, and developers with basic knowledge of Python. It is also suitable for educators looking to incorporate deep learning into their curriculum. The practical examples and step-by-step exercises make it accessible for those who may not have a strong background in mathematics or statistics, enabling them to grasp complex concepts easily.

What prior knowledge is recommended before reading this book?

Readers are encouraged to have a foundational understanding of Python programming and basic concepts of machine learning. Familiarity with libraries such as NumPy and Pandas will enhance the learning experience. Having a grasp of fundamental mathematics, particularly linear algebra and calculus, can be beneficial, as some concepts in deep learning build on these principles, helping readers understand model behaviors more profoundly.

What type of projects are included in the book?

The book includes various hands-on projects that demonstrate the applicability of deep learning across different domains. Examples range from building neural networks for image classification to creating models for text generation. These projects not only illustrate theoretical concepts but also provide a practical framework for readers to implement their own deep learning solutions in real applications like chatbots and recommendation systems.

Is 'Practical Deep Learning' suitable for beginners?

Yes, this book is specifically designed to cater to beginners in deep learning. It breaks down complex topics into digestible segments, starting from the basics and gradually progressing to advanced topics. Each chapter builds upon the previous one while providing ample exercises that reinforce learning, ensuring that even those new to the field can grasp essential concepts and techniques confidently.

What tools or software do I need to follow along with the book?

To effectively engage with the content, readers should have access to a development environment such as Jupyter Notebook or any IDE that supports Python. Additionally, installing libraries like TensorFlow or PyTorch will be necessary for executing the provided code examples. These tools will enable learners to experiment with code and improve their understanding of how different deep learning models work.

Can this book help me transition to a career in data science?

Absolutely. 'Practical Deep Learning: A Python-Based Introduction' equips readers with valuable skills and knowledge that are highly sought after in the field of data science. By completing the practical exercises and projects, readers not only enhance their portfolio but also build confidence in applying deep learning techniques, making them stronger candidates for roles in data analysis, machine learning engineering, and artificial intelligence.

Does the book require a specific version of Python?

The book is generally compatible with Python 3. It is recommended for readers to use Python 3.x to ensure compatibility with the latest packages used throughout the text. Keeping your Python and essential libraries up to date will eliminate potential issues with syntax differences or deprecated functions, ensuring a smoother experience as you follow along with the examples.

What distinguishes this book from other deep learning books?

What sets this book apart is its practical, application-oriented approach. While many texts focus on theoretical aspects, this book prioritizes real-world implementations, making it particularly valuable for readers who prefer learning by doing. The inclusion of diverse projects spanning various industries allows readers to see the direct impact of deep learning, enhancing both understanding and retention of the material.

Is Practical Deep Learning: A Python-Based Introduction Available to Shop Online in Switzerland?

Yes, at Ubuy Switzerland this product is available for you to shop at a reasonable price. The Practical Deep Learning: A Python-Based Introduction is not available locally but you can trust us with our express shipping services.

How Long Does It Take to Get Product After Placing the Order?

The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.

Practical Deep Learning: A Python-Based Introduction

Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects

Item #: 25664725

Practical Deep Learning: A Python-Based Introduction

Q: Where can I buy 'Practical Deep Learning: A Python-Based Introduction' in Switzerland?

You can purchase 'Practical Deep Learning: A Python-Based Introduction' from Ubuy in Switzerland. Ubuy offers a user-friendly shopping experience, making it easy to find the book and access additional resources related to deep learning and Python programming.

89% of respondents would recommend this to a friend

Item #: 25664725

CHF 60

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

^{*All items will import from US}

Availability : In stock

Imported from USA store

QTY:

Order now and get it around Sunday, October 18

Secured transaction

Our Top Logistics Partners

Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects

U-Care Warranty:

None

Select a Plan

Fast
Shipping

Free
Return^*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

Note: Step Down Voltage Transformer required for using electronics products of US store (110-120). Recommended power converters Buy Now.

What Stands Out

Hands-On Learning

Engages learners through practical exercises, allowing users to apply deep learning concepts directly in Python, enhancing retention and understanding for aspiring data scientists.

Accessible Content

Designed for beginners, the book simplifies complex topics, making deep learning approachable without compromising on technical depth, perfect for those new to the field.

Real-World Applications

Focuses on practical use cases in industry, equipping readers with skills to solve actual problems in data-driven environments, increasing their job readiness and relevance.

Product Details

Teaches beginners how to build datasets and models for training neural networks
Focuses on the subfield of machine learning known as deep learning
Explains core concepts and provides a foundation to start building models
Requires basic familiarity with computer programming and high school math
Covers topics such as building a good training dataset and using libraries like scikit-learn and Keras
Includes how to use classic machine learning models, neural networks, and convolutional neural networks

Publisher	No Starch Press
Publication date	February 23, 2021
Language	English
Print length	464 pages
ISBN-10	1718500742
ISBN-13	978-1718500747
Item Weight	1.71 pounds (780 grams)
Dimensions	7.13 x 0.94 x 9.25 inches (18.1 x 2.4 x 23.5 cm)

Who Should Buy?

Beginners in AI
Ideal for those new to artificial intelligence, offering a hands-on approach to deep learning concepts with Python.
Data Science Students
Perfect for students looking to build a strong foundational understanding of deep learning techniques using practical examples.
Professionals Upskilling
Great for professionals seeking to enhance their data science skills by learning deep learning with practical Python applications.

Experienced Practitioners
May not offer sufficient depth or challenge for seasoned professionals already well-versed in deep learning methods.

Product Description

Practical Deep Learning: A Python-Based Introduction

Have any Query? Chat with us

Customer Questions & Answers

Question: How to Shop Practical Deep Learning: A Python-Based Introduction Online From Ubuy?

Answer: It’s easy to shop Practical Deep Learning: A Python-Based Introduction online from Ubuy. You just have to search for the product, choose your shipping method while checking out and get it delivered to your location.
Question: Is Practical Deep Learning: A Python-Based Introduction Available to Shop Online in Switzerland?

Answer: Yes, at Ubuy Switzerland this product is available for you to shop at a reasonable price. The Practical Deep Learning: A Python-Based Introduction is not available locally but you can trust us with our express shipping services.
Question: How Long Does It Take to Get Product After Placing the Order?

Answer: The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.

Neural Networks Editorial Review

The book "Deep Learning with Python" by Francois Chollet is a practical guidebook for those who want to run sophisticated analysis without a complex theoretical background. The style of the book is semi-conversational and anecdotal, making it easy to be read and understood for those who do not have much experience with deep learning. The author also provides code examples that produce graphical output and simple statistics to help readers develop intuition to compare different methods.

Customer Reviews & Ratings

5.0

1 customers ratings

5 Star

100%
4 Star

0%
3 Star

0%
2 Star

0%
1 Star

0%

Review this product

Share your thoughts with other customers

Pros

The book provides practical and useful information for deep learning beginners.
The conversational tone and anecdotal style make it easy to read and understand.
The author provides code examples with graphical output and simple statistics to help readers understand what they are doing.
It's a good resource for those who need proper learning and reading on the topic.

Cons

One reviewer pointed out that the author didn't take any of the applications from beginning to end, which doesn't help readers a lot. Note: There were a few reviews; only those that provided relevant information were used in creating the review.

Product Price History

Important information

Limitations : For products shipped internationally, please note that any manufacturer warranty may not be valid; manufacturer service options may not be available; product manuals, instructions, and safety warnings may not be in destination country languages; the products (and accompanying materials) may not be designed in accordance with destination country standards, specifications, and labeling requirements; and the products may not conform to destination country voltage and other electrical standards (requiring use of an adapter or converter if appropriate). The recipient is responsible for assuring that the product can be lawfully imported to the destination country. When ordering from Ubuy or its affiliates, the recipient is the importer of record and must comply with all laws and regulations of the destination country.
Not all the products listed on Ubuy are for sale, as Ubuy is a global search engine. Products are subject to export/trade regulations.

CHF 60

Order now and get it around Sunday, October 18

QTY:

Secured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners

Fastest cross-border delivery

Features & Benefits

Explains core concepts of deep learning
Learn to build a good training dataset
Develop a successful deep learning model from scratch
Conduct experiments along the way
Perfect introduction for beginners
Gain skills and confidence to start your own machine learning projects

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns ^*, and secure packaging on every order.

Practical Deep Learning: A Python-Based Introduction

CHF 60

Fast Shipping

Free Return*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

What Stands Out

Product Details

Who Should Buy?

Product Description

Customer Questions & Answers

Neural Networks Editorial Review

Customer Reviews & Ratings

Review this product

Pros

Cons

Product Price History

Important information

CHF 60

Features & Benefits

Ubuy Assurance

Fast
Shipping

Free
Return^*